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Racial composition, unemployment, and crime: dealing with inconsistencies in panel designs
1Criminology Program, The University of Texas at Dallas, 800 West Campbell Road, Richardson, TX 75080-3021, USA. worrall@utdallas.edu
Social Science Research
|December 17, 2008
Summary
This study examines how racial composition and unemployment affect crime rates. Using a novel decomposition method, it reveals these factors become significant predictors when accounting for their slow-moving nature in panel data analysis.
Area of Science:
- Criminology
- Sociology
- Political Science
Background:
- Racial composition and unemployment are frequently studied in relation to crime.
- Previous research shows inconsistent findings, particularly in panel analyses with unit fixed effects.
- This inconsistency may stem from the slow-moving nature of these variables, causing collinearity issues.
Purpose of the Study:
- To investigate the inconsistent statistical significance of racial composition and unemployment in crime studies.
- To address the challenges posed by slow-moving variables in panel data analysis.
- To demonstrate a method for accurately estimating the effects of time-invariant or rarely changing variables.
Main Methods:
- Review of pertinent studies on crime, racial composition, and unemployment.
- Application of a fixed effects vector decomposition procedure.
- Analysis of how slow-moving variables behave in panel data with unit fixed effects.
Main Results:
- Racial composition (percent black) and unemployment (percent unemployed) have historically shown inconsistent results in crime research.
- When accounting for the slow-moving nature of these variables using fixed effects vector decomposition, their coefficients appear positive and significant.
- The proposed method helps resolve collinearity issues between slow-moving variables and unit fixed effects.
Conclusions:
- The fixed effects vector decomposition procedure offers a more accurate estimation of the relationship between crime and variables like racial composition and unemployment.
- This method clarifies the impact of these sociodemographic factors by properly isolating their effects from time-invariant characteristics.
- Future research should consider employing similar decomposition techniques to better understand the dynamics of crime determinants.
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